Salesforce is going all in on AI, with Agentforce leading the charge. But while the promise of AI-powered automation and intelligent agents is exciting, there’s a catch: AI isn’t a magic switch you can flip on. For AI to deliver on its potential, your Salesforce environment must be AI-ready—and that starts with data.

But data alone isn’t enough. Metadata, the structure and relationships that define your Salesforce instance, is just as critical. It provides the framework that connects objects, automations, and workflows, giving both teams and AI-powered systems the necessary context to operate effectively.

Without a solid foundation—clean data, well-structured metadata, and clear processes—even the most advanced AI tools will fall short. But what does that mean for your organization? More importantly, how can you ensure your Salesforce environment is AI-ready?

The AI revolution in Salesforce

With the launch of Agentforce in December 2024, Salesforce is moving beyond predictive and generative AI to an agentic approach, where autonomous AI agents can take action across sales, service, and marketing functions.

Salesforce’s previous AI tool, Einstein, was primarily predictive AI, helping businesses analyze past data for insights like Lead Scoring and Opportunity Insights. While this was useful, it was still reactive—predicting outcomes based on historical data rather than acting on those predictions.

Now, Agentforce takes things a step further, incorporating generative AI and autonomous agents that can act in real-time to optimize business processes. These agents leverage generative AI and automation to optimize business processes in real-time, handling tasks like customer interactions, sales routing, and service case resolutions without human intervention.

This shift is more than just an exciting innovation; it’s reshaping how Salesforce operates. According to Bloomberg, Salesforce recently laid off over 1,000 employees while simultaneously hiring for AI-focused roles, a clear indication that the company is doubling down on its AI strategy.

Marc Benioff, CEO of Salesforce, reinforced this vision, stating:

“We’re going to be building custom agents for so many of you as well with Agentforce because it’s a development platform as well as this incredible capability to radically extend your sales and service organizations.”

In other words, Salesforce isn’t just providing pre-built AI tools—it’s offering a platform for businesses to create AI-driven custom agents tailored to their specific needs. These agents will extend across multiple functions, fundamentally changing how businesses interact with customers, automate processes, and drive revenue growth.

Benioff has been vocal about the importance of data quality in AI, particularly when comparing Agentforce to AI offerings from competitors like Microsoft. He didn’t hold back in criticizing Microsoft’s AI approach:

“I just think Microsoft has done such a disservice to the whole industry with how they’ve positioned AI. I even bought it, but then I’m using it and it’s not grounded into any of my data, it doesn’t have any levels of accuracy, it was spilling data for me!”

His point is clear: AI is only as good as the data it operates on. Without structured, accurate, and well-orchestrated data, AI tools, no matter how powerful, will fail to deliver meaningful results.

For businesses looking to harness Agentforce, this highlights a crucial takeaway: AI must be positioned with data, and that data must be meticulously organized. Metadata, the framework that defines how data is structured in Salesforce, needs to be clean, consistent, and AI-ready. Without this foundation, AI-driven automation will be unreliable, inefficient, and prone to errors.